Overview

Dataset statistics

Number of variables29
Number of observations1867
Missing cells13555
Missing cells (%)25.0%
Duplicate rows6
Duplicate rows (%)0.3%
Total size in memory423.1 KiB
Average record size in memory232.1 B

Variable types

NUM16
CAT11
UNSUPPORTED1
BOOL1

Warnings

Dataset has 6 (0.3%) duplicate rows Duplicates
UArt2 has 1598 (85.6%) missing values Missing
AUrs1 has 1676 (89.8%) missing values Missing
AUrs2 has 1856 (99.4%) missing values Missing
AufHi has 1417 (75.9%) missing values Missing
Char1 has 1710 (91.6%) missing values Missing
Char2 has 1825 (97.8%) missing values Missing
Lich2 has 1506 (80.7%) missing values Missing
Zust2 has 1850 (99.1%) missing values Missing
Fstf has 109 (5.8%) missing values Missing
WoTag is an unsupported type, check if it needs cleaning or further analysis Unsupported
TempDist has 858 (46.0%) zeros Zeros
SpatDist has 1584 (84.8%) zeros Zeros
UArt1 has 64 (3.4%) zeros Zeros

Reproduction

Analysis started2020-11-03 22:46:26.933258
Analysis finished2020-11-03 22:47:05.733158
Duration38.8 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

TempMax
Real number (ℝ≥0)

Distinct211
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.0091055
Minimum9
Maximum1341
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:06.130845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile24
Q169
median117
Q3216
95-th percentile525
Maximum1341
Range1332
Interquartile range (IQR)147

Descriptive statistics

Standard deviation173.2912269
Coefficient of variation (CV)0.9901840616
Kurtosis9.396857376
Mean175.0091055
Median Absolute Deviation (MAD)63
Skewness2.581777376
Sum326742
Variance30029.84933
MonotocityNot monotonic
2020-11-03T23:47:06.296968image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
84361.9%
 
81361.9%
 
93351.9%
 
87331.8%
 
72311.7%
 
111311.7%
 
78311.7%
 
54311.7%
 
69311.7%
 
96301.6%
 
Other values (201)154282.6%
 
ValueCountFrequency (%) 
980.4%
 
12110.6%
 
15130.7%
 
18281.5%
 
21201.1%
 
ValueCountFrequency (%) 
134110.1%
 
132330.2%
 
125720.1%
 
119410.1%
 
115210.1%
 

TempAvg
Real number (ℝ≥0)

Distinct246
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.23245849
Minimum3
Maximum1326
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:06.465915image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile11
Q132
median55
Q390
95-th percentile196
Maximum1326
Range1323
Interquartile range (IQR)58

Descriptive statistics

Standard deviation81.24420703
Coefficient of variation (CV)1.094456639
Kurtosis72.03526142
Mean74.23245849
Median Absolute Deviation (MAD)28
Skewness6.318025592
Sum138592
Variance6600.621175
MonotocityNot monotonic
2020-11-03T23:47:06.626565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
44301.6%
 
26271.4%
 
48271.4%
 
53261.4%
 
59261.4%
 
24251.3%
 
56241.3%
 
57231.2%
 
50231.2%
 
47231.2%
 
Other values (236)161386.4%
 
ValueCountFrequency (%) 
310.1%
 
430.2%
 
5110.6%
 
6130.7%
 
7181.0%
 
ValueCountFrequency (%) 
132610.1%
 
126010.1%
 
95510.1%
 
92010.1%
 
70310.1%
 

SpatMax
Real number (ℝ≥0)

Distinct1517
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12099.28388
Minimum832
Maximum219082
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:06.797774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum832
5-th percentile1899.3
Q14518.5
median8422
Q314539
95-th percentile31525.9
Maximum219082
Range218250
Interquartile range (IQR)10020.5

Descriptive statistics

Standard deviation17042.85808
Coefficient of variation (CV)1.408584033
Kurtosis82.68306322
Mean12099.28388
Median Absolute Deviation (MAD)4623
Skewness7.967522598
Sum22589363
Variance290459011.6
MonotocityNot monotonic
2020-11-03T23:47:06.948094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1316380.4%
 
18973050.3%
 
662150.3%
 
235150.3%
 
347550.3%
 
1511740.2%
 
484040.2%
 
3549240.2%
 
1345640.2%
 
602540.2%
 
Other values (1507)181997.4%
 
ValueCountFrequency (%) 
83220.1%
 
96510.1%
 
97110.1%
 
100010.1%
 
103610.1%
 
ValueCountFrequency (%) 
21908230.2%
 
19531020.1%
 
18973050.3%
 
15323710.1%
 
13578010.1%
 

SpatAvg
Real number (ℝ≥0)

Distinct1498
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3996.387788
Minimum135
Maximum17805
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:07.095647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile1053.3
Q12007.5
median3402
Q35334.5
95-th percentile9279
Maximum17805
Range17670
Interquartile range (IQR)3327

Descriptive statistics

Standard deviation2621.118875
Coefficient of variation (CV)0.655872006
Kurtosis2.208051196
Mean3996.387788
Median Absolute Deviation (MAD)1569
Skewness1.329804557
Sum7461256
Variance6870264.157
MonotocityNot monotonic
2020-11-03T23:47:07.245317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1026650.3%
 
141350.3%
 
560650.3%
 
882240.2%
 
1236340.2%
 
442340.2%
 
752730.2%
 
147530.2%
 
641530.2%
 
793330.2%
 
Other values (1488)182897.9%
 
ValueCountFrequency (%) 
13510.1%
 
34710.1%
 
35810.1%
 
38710.1%
 
39310.1%
 
ValueCountFrequency (%) 
1780510.1%
 
1685110.1%
 
1657120.1%
 
1552610.1%
 
1513210.1%
 

TempDist
Real number (ℝ≥0)

ZEROS

Distinct25
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.538832351
Minimum0
Maximum24
Zeros858
Zeros (%)46.0%
Memory size14.6 KiB
2020-11-03T23:47:07.395878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile21
Maximum24
Range24
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.888638558
Coefficient of variation (CV)1.243698693
Kurtosis0.1675782571
Mean5.538832351
Median Absolute Deviation (MAD)3
Skewness1.112474575
Sum10341
Variance47.45334119
MonotocityNot monotonic
2020-11-03T23:47:07.521681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
085846.0%
 
6894.8%
 
7764.1%
 
5703.7%
 
8683.6%
 
9663.5%
 
10603.2%
 
3583.1%
 
12512.7%
 
4502.7%
 
Other values (15)42122.5%
 
ValueCountFrequency (%) 
085846.0%
 
1412.2%
 
2321.7%
 
3583.1%
 
4502.7%
 
ValueCountFrequency (%) 
24281.5%
 
23211.1%
 
22271.4%
 
21311.7%
 
20191.0%
 

SpatDist
Real number (ℝ≥0)

ZEROS

Distinct220
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.7728977
Minimum0
Maximum2000
Zeros1584
Zeros (%)84.8%
Memory size14.6 KiB
2020-11-03T23:47:07.782984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile650
Maximum2000
Range2000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation280.5631239
Coefficient of variation (CV)3.309585157
Kurtosis18.59098594
Mean84.7728977
Median Absolute Deviation (MAD)0
Skewness4.169201904
Sum158271
Variance78715.66651
MonotocityNot monotonic
2020-11-03T23:47:07.931332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0158484.8%
 
250150.8%
 
75080.4%
 
125060.3%
 
5030.2%
 
15130.2%
 
29030.2%
 
17030.2%
 
46820.1%
 
34120.1%
 
Other values (210)23812.7%
 
ValueCountFrequency (%) 
0158484.8%
 
210.1%
 
320.1%
 
710.1%
 
1310.1%
 
ValueCountFrequency (%) 
200020.1%
 
197510.1%
 
196010.1%
 
194910.1%
 
190610.1%
 

Coverage
Real number (ℝ≥0)

Distinct96
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.58543117
Minimum2
Maximum100
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:08.091429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile13
Q127
median41
Q358
95-th percentile85
Maximum100
Range98
Interquartile range (IQR)31

Descriptive statistics

Standard deviation21.43115206
Coefficient of variation (CV)0.4917044866
Kurtosis-0.363760615
Mean43.58543117
Median Absolute Deviation (MAD)15
Skewness0.4941271419
Sum81374
Variance459.2942785
MonotocityNot monotonic
2020-11-03T23:47:08.243629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
42452.4%
 
30422.2%
 
36422.2%
 
44412.2%
 
25402.1%
 
40402.1%
 
31392.1%
 
37382.0%
 
18372.0%
 
45361.9%
 
Other values (86)146778.6%
 
ValueCountFrequency (%) 
230.2%
 
350.3%
 
560.3%
 
660.3%
 
760.3%
 
ValueCountFrequency (%) 
100181.0%
 
9830.2%
 
9720.1%
 
9640.2%
 
9530.2%
 

TLCar
Real number (ℝ≥0)

Distinct828
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1510.77022
Minimum1000
Maximum1999
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:08.388491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1052
Q11263
median1518
Q31764
95-th percentile1948
Maximum1999
Range999
Interquartile range (IQR)501

Descriptive statistics

Standard deviation288.4265018
Coefficient of variation (CV)0.1909135473
Kurtosis-1.208499076
Mean1510.77022
Median Absolute Deviation (MAD)250
Skewness-0.03924223406
Sum2820608
Variance83189.84696
MonotocityNot monotonic
2020-11-03T23:47:08.529524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
117170.4%
 
129370.4%
 
119170.4%
 
195570.4%
 
190270.4%
 
199960.3%
 
140360.3%
 
147260.3%
 
186660.3%
 
167860.3%
 
Other values (818)180296.5%
 
ValueCountFrequency (%) 
100010.1%
 
100150.3%
 
100220.1%
 
100330.2%
 
100630.2%
 
ValueCountFrequency (%) 
199960.3%
 
199830.2%
 
199720.1%
 
199630.2%
 
199420.1%
 

TLHGV
Real number (ℝ≥0)

Distinct488
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean746.8339582
Minimum500
Maximum999
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:08.673894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile525.3
Q1620
median743
Q3871
95-th percentile972
Maximum999
Range499
Interquartile range (IQR)251

Descriptive statistics

Standard deviation144.8114466
Coefficient of variation (CV)0.193900458
Kurtosis-1.233212315
Mean746.8339582
Median Absolute Deviation (MAD)126
Skewness0.03726417494
Sum1394339
Variance20970.35505
MonotocityNot monotonic
2020-11-03T23:47:08.816154image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
926110.6%
 
582100.5%
 
871100.5%
 
869100.5%
 
62690.5%
 
79590.5%
 
56790.5%
 
98290.5%
 
57990.5%
 
66490.5%
 
Other values (478)177294.9%
 
ValueCountFrequency (%) 
50030.2%
 
50170.4%
 
50230.2%
 
50310.1%
 
50410.1%
 
ValueCountFrequency (%) 
99950.3%
 
99840.2%
 
99710.1%
 
99630.2%
 
99530.2%
 

Strasse
Categorical

Distinct17
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
A3
574 
A9
466 
A96
156 
A7
130 
A73
129 
Other values (12)
412 
ValueCountFrequency (%) 
A357430.7%
 
A946625.0%
 
A961568.4%
 
A71307.0%
 
A731296.9%
 
A61276.8%
 
A991166.2%
 
A92663.5%
 
A94372.0%
 
A70311.7%
 
Other values (7)351.9%
 
2020-11-03T23:47:08.974983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.1%
2020-11-03T23:47:09.115017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.30690948
Min length2

Kat
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
3
890 
7
724 
2
217 
1
 
36
ValueCountFrequency (%) 
389047.7%
 
772438.8%
 
221711.6%
 
1361.9%
 
2020-11-03T23:47:09.246782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:09.328164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:09.453321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Typ
Real number (ℝ≥0)

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.054097483
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:09.550141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median6
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.94780996
Coefficient of variation (CV)0.385392242
Kurtosis0.214578889
Mean5.054097483
Median Absolute Deviation (MAD)0
Skewness-1.388058215
Sum9436
Variance3.793963641
MonotocityNot monotonic
2020-11-03T23:47:09.647310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
6131370.3%
 
130116.1%
 
31206.4%
 
71186.3%
 
5110.6%
 
440.2%
 
ValueCountFrequency (%) 
130116.1%
 
31206.4%
 
440.2%
 
5110.6%
 
6131370.3%
 
ValueCountFrequency (%) 
71186.3%
 
6131370.3%
 
5110.6%
 
440.2%
 
31206.4%
 

Betei
Real number (ℝ≥0)

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.275307981
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:09.758599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum18
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9596611188
Coefficient of variation (CV)0.4217719654
Kurtosis42.98696399
Mean2.275307981
Median Absolute Deviation (MAD)0
Skewness3.808235232
Sum4248
Variance0.920949463
MonotocityNot monotonic
2020-11-03T23:47:09.856871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
2114561.3%
 
335819.2%
 
121911.7%
 
41035.5%
 
5251.3%
 
760.3%
 
660.3%
 
840.2%
 
1810.1%
 
ValueCountFrequency (%) 
121911.7%
 
2114561.3%
 
335819.2%
 
41035.5%
 
5251.3%
 
ValueCountFrequency (%) 
1810.1%
 
840.2%
 
760.3%
 
660.3%
 
5251.3%
 

UArt1
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.38189609
Minimum0
Maximum9
Zeros64
Zeros (%)3.4%
Memory size14.6 KiB
2020-11-03T23:47:09.973867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.438164325
Coefficient of variation (CV)0.7209459606
Kurtosis0.3529952481
Mean3.38189609
Median Absolute Deviation (MAD)1
Skewness1.283502637
Sum6314
Variance5.944645278
MonotocityNot monotonic
2020-11-03T23:47:10.076329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
283844.9%
 
345324.3%
 
81658.8%
 
91256.7%
 
5904.8%
 
1874.7%
 
0643.4%
 
7351.9%
 
660.3%
 
440.2%
 
ValueCountFrequency (%) 
0643.4%
 
1874.7%
 
283844.9%
 
345324.3%
 
440.2%
 
ValueCountFrequency (%) 
91256.7%
 
81658.8%
 
7351.9%
 
660.3%
 
5904.8%
 

UArt2
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)3.3%
Missing1598
Missing (%)85.6%
Infinite0
Infinite (%)0.0%
Mean7.200743494
Minimum0
Maximum9
Zeros4
Zeros (%)0.2%
Memory size14.6 KiB
2020-11-03T23:47:10.184809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median8
Q39
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.667633427
Coefficient of variation (CV)0.3704663872
Kurtosis0.0285595817
Mean7.200743494
Median Absolute Deviation (MAD)1
Skewness-1.288913445
Sum1937
Variance7.116268102
MonotocityNot monotonic
2020-11-03T23:47:10.286781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
91337.1%
 
8693.7%
 
3392.1%
 
2120.6%
 
150.3%
 
040.2%
 
740.2%
 
520.1%
 
410.1%
 
(Missing)159885.6%
 
ValueCountFrequency (%) 
040.2%
 
150.3%
 
2120.6%
 
3392.1%
 
410.1%
 
ValueCountFrequency (%) 
91337.1%
 
8693.7%
 
740.2%
 
520.1%
 
410.1%
 

AUrs1
Real number (ℝ≥0)

MISSING

Distinct14
Distinct (%)7.3%
Missing1676
Missing (%)89.8%
Infinite0
Infinite (%)0.0%
Mean76.23560209
Minimum72
Maximum89
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:10.503496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum72
5-th percentile72
Q173
median73
Q381
95-th percentile89
Maximum89
Range17
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.010691311
Coefficient of variation (CV)0.07884362615
Kurtosis-0.05234210446
Mean76.23560209
Median Absolute Deviation (MAD)1
Skewness1.279196596
Sum14561
Variance36.12841003
MonotocityNot monotonic
2020-11-03T23:47:10.608218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
73955.1%
 
72412.2%
 
89181.0%
 
82130.7%
 
8880.4%
 
8140.2%
 
8630.2%
 
7520.1%
 
8320.1%
 
8710.1%
 
Other values (4)40.2%
 
(Missing)167689.8%
 
ValueCountFrequency (%) 
72412.2%
 
73955.1%
 
7520.1%
 
7610.1%
 
7710.1%
 
ValueCountFrequency (%) 
89181.0%
 
8880.4%
 
8710.1%
 
8630.2%
 
8410.1%
 

AUrs2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)54.5%
Missing1856
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean78.54545455
Minimum73
Maximum89
Zeros0
Zeros (%)0.0%
Memory size14.6 KiB
2020-11-03T23:47:10.716083image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile73
Q174
median80
Q381
95-th percentile86.5
Maximum89
Range16
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.222329679
Coefficient of variation (CV)0.06648799359
Kurtosis-0.2067511111
Mean78.54545455
Median Absolute Deviation (MAD)5
Skewness0.6349656579
Sum864
Variance27.27272727
MonotocityNot monotonic
2020-11-03T23:47:10.805638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
7330.2%
 
8120.1%
 
7520.1%
 
8020.1%
 
8910.1%
 
8410.1%
 
(Missing)185699.4%
 
ValueCountFrequency (%) 
7330.2%
 
7520.1%
 
8020.1%
 
8120.1%
 
8410.1%
 
ValueCountFrequency (%) 
8910.1%
 
8410.1%
 
8120.1%
 
8020.1%
 
7520.1%
 

AufHi
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)1.8%
Missing1417
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean3.208888889
Minimum0
Maximum9
Zeros2
Zeros (%)0.1%
Memory size14.6 KiB
2020-11-03T23:47:10.911549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q13
median3
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7585657027
Coefficient of variation (CV)0.2363951289
Kurtosis25.9572532
Mean3.208888889
Median Absolute Deviation (MAD)0
Skewness3.843828503
Sum1444
Variance0.5754219253
MonotocityNot monotonic
2020-11-03T23:47:11.002471image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
338120.4%
 
4442.4%
 
5160.9%
 
830.2%
 
020.1%
 
920.1%
 
210.1%
 
110.1%
 
(Missing)141775.9%
 
ValueCountFrequency (%) 
020.1%
 
110.1%
 
210.1%
 
338120.4%
 
4442.4%
 
ValueCountFrequency (%) 
920.1%
 
830.2%
 
5160.9%
 
4442.4%
 
338120.4%
 

Alkoh
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
0
1842 
1
 
25
ValueCountFrequency (%) 
0184298.7%
 
1251.3%
 
2020-11-03T23:47:11.074099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Char1
Categorical

MISSING

Distinct4
Distinct (%)2.5%
Missing1710
Missing (%)91.6%
Memory size14.6 KiB
5
60 
4
56 
6
33 
2
ValueCountFrequency (%) 
5603.2%
 
4563.0%
 
6331.8%
 
280.4%
 
(Missing)171091.6%
 
2020-11-03T23:47:11.160202image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:11.237117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:11.351172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Char2
Categorical

MISSING

Distinct1
Distinct (%)2.4%
Missing1825
Missing (%)97.8%
Memory size14.6 KiB
6
42 
ValueCountFrequency (%) 
6422.2%
 
(Missing)182597.8%
 
2020-11-03T23:47:11.464118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:11.538286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:11.610006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Lich1
Categorical

Distinct3
Distinct (%)0.2%
Missing3
Missing (%)0.2%
Memory size14.6 KiB
0
1503 
2
263 
1
 
98
ValueCountFrequency (%) 
0150380.5%
 
226314.1%
 
1985.2%
 
(Missing)30.2%
 
2020-11-03T23:47:11.727338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:11.808114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:11.908220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Lich2
Categorical

MISSING

Distinct2
Distinct (%)0.6%
Missing1506
Missing (%)80.7%
Memory size14.6 KiB
4
345 
3
 
16
ValueCountFrequency (%) 
434518.5%
 
3160.9%
 
(Missing)150680.7%
 
2020-11-03T23:47:12.023721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:12.102446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:12.189323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Zust1
Categorical

Distinct3
Distinct (%)0.2%
Missing5
Missing (%)0.3%
Memory size14.6 KiB
0
1408 
1
414 
2
 
40
ValueCountFrequency (%) 
0140875.4%
 
141422.2%
 
2402.1%
 
(Missing)50.3%
 
2020-11-03T23:47:12.303351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:12.385956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:12.475365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Zust2
Categorical

MISSING

Distinct1
Distinct (%)5.9%
Missing1850
Missing (%)99.1%
Memory size14.6 KiB
2
17 
ValueCountFrequency (%) 
2170.9%
 
(Missing)185099.1%
 
2020-11-03T23:47:12.584148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:12.664205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:12.732976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Fstf
Categorical

MISSING

Distinct7
Distinct (%)0.4%
Missing109
Missing (%)5.8%
Memory size14.6 KiB
2
809 
1
587 
3
292 
4
 
39
S
 
23
Other values (2)
 
8
ValueCountFrequency (%) 
280943.3%
 
158731.4%
 
329215.6%
 
4392.1%
 
S231.2%
 
550.3%
 
F30.2%
 
(Missing)1095.8%
 
2020-11-03T23:47:12.855462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:12.948592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:13.086054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.116764863
Min length1

WoTag
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size14.7 KiB

FeiTag
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
0
1803 
1
 
47
-1
 
17
ValueCountFrequency (%) 
0180396.6%
 
1472.5%
 
-1170.9%
 
2020-11-03T23:47:13.212291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:13.293044image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:13.386299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length1
Mean length1.009105517
Min length1

Month
Categorical

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
Jul
242 
Aug
222 
Oct
167 
Sep
163 
Jun
163 
Other values (7)
910 
ValueCountFrequency (%) 
Jul24213.0%
 
Aug22211.9%
 
Oct1678.9%
 
Sep1638.7%
 
Jun1638.7%
 
Apr1508.0%
 
Mar1427.6%
 
Nov1417.6%
 
May1407.5%
 
Dec1377.3%
 
Other values (2)20010.7%
 
2020-11-03T23:47:13.621276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-03T23:47:13.743136image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Interactions

2020-11-03T23:46:32.074750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:33.182624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:33.293566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:33.400835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:33.526787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:33.641604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:34.762869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:34.872461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:34.991481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.096378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.201242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.310705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.416292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.525946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.633465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.731212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.842317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:35.946843image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.054864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.154074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.258402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.362904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.465960image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.571417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.681744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.778808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:36.880828image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.104466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.209877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.311146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.412792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.521100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.625935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.717909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.814262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:37.908186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.005301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.098687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.183872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.266318image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.363329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.453347image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.540072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.637353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.732628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.823789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:38.925002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.024343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.133013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.256778image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.373036image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.492346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.612604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.722077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.823139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:39.937170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.066562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.185408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.300328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.538832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.665581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.810777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:40.980768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.123353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.245562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.384914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.507594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.617682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.722417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:41.824819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.022827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.161291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.309086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.418801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.523203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.651209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.757766image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.858603image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:42.960602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.060154image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.166786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.272364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.384186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.505612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.625789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.747784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.855187image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:43.949290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.071670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.194522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.295468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.516110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.630620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.734001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.847272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:44.956184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.072166image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.181559image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.288588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.386885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.494762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.598888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.694546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.790015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.899606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:45.992285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.086909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.186908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.287772image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.386975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.494636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.598138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.701503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.810160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:46.930923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.059993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.187481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.310796image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.422885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.543599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.670761image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.773820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.875194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:47.982014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.201175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.308012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.410928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.515302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.632390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.724085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.819599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:48.908285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.005251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.100113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.199004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.283892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.383123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.476526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.568856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.662169image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.755413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.855877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:49.949206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.044186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.138831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.248888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.366410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.467228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.579356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.679156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.769854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.853879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:50.954890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.051503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.153162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.249090image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.343177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.560778image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.662635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.754190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.851077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:51.952001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.058131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.162646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.269060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.371213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.464705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.559644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.666975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.781361image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:52.902150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.004358image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.113065image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.243894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.366344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.471149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.581058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.712276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.838553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:53.969232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.099877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.241028image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.359685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.470880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.588375image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.692785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.807069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:54.916611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.023121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.232093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.338550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.444362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.570996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.682038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.798914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:55.910331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.026267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.132803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.227607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.321524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.428609image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.527730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.634381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.744957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.850419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:56.952705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.064625image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.155527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.250656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.346482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.446169image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.545536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.646323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.743553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.832628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:57.930696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.047383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.150890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.254139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.362634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.475655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.577789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.803556image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:58.907755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.015703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.115617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.246446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.353237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.473456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.587724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.697363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.801735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:46:59.918410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.026723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.126672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.225081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.325404image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.419025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.514109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.610221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.710472image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.830752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:00.955948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.073886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.186336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.308209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.423033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.539477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.667693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.779345image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:01.897824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:02.013721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:02.136119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:02.241383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:02.338287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:02.556452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-03T23:47:13.877310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-03T23:47:14.199349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-03T23:47:14.499276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-03T23:47:14.810319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-03T23:47:15.082017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-03T23:47:02.897212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:04.512999image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:05.214524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-03T23:47:05.494706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

TempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTLCarTLHGVStrasseKatTypBeteiUArt1UArt2AUrs1AUrs2AufHiAlkohChar1Char2Lich1Lich2Zust1Zust2FstfWoTagFeiTagMonth
03602226568431100611714718A32132NaNNaNNaNNaN0NaNNaN0.0NaN1.0NaN2Di1Jan
1692860003475100411691686A63632NaN89.0NaNNaN0NaNNaN0.0NaN0.0NaN2Di1Jan
21628913925721200501293804A336529.0NaNNaN3.00NaNNaN0.0NaN1.0NaN2Mi0Jan
3162891392572121996501293804A33672NaN82.0NaNNaN0NaNNaN0.0NaN1.0NaN2Mi0Jan
41624920701584700281417502A33622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaNNaNMi0Jan
545207483305700421044780A63632NaNNaNNaNNaN1NaNNaN0.0NaN0.0NaN1Mi0Jan
628511718067506800281205643A97133NaN72.0NaNNaN0NaNNaN0.0NaN1.02.01Mi-1Jan
721696129915615110431647670A33733NaNNaNNaNNaN0NaNNaN2.04.01.0NaN2Do0Jan
8138556415314200421803985A97123NaNNaNNaNNaN0NaNNaN2.04.00.0NaN1Fr0Jan
910561994125550112221657905A93632NaNNaNNaNNaN0NaNNaN2.04.01.0NaN4Fr0Jan

Last rows

TempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTLCarTLHGVStrasseKatTypBeteiUArt1UArt2AUrs1AUrs2AufHiAlkohChar1Char2Lich1Lich2Zust1Zust2FstfWoTagFeiTagMonth
185781612698236080861305511A73119NaNNaNNaN3.006.0NaN2.04.00.0NaN2Fr0Dec
18582375229229630500211269784A93632NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaNFFr0Dec
18595649443244704700161785638A731429.0NaNNaN3.00NaNNaN0.0NaN0.0NaN2-10Dec
186020193149994372160291875579A73622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1Sa0Dec
1861452639552768220751262925A93622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1So0Dec
186239311345610007110741850582A93734NaNNaNNaNNaN0NaNNaN2.04.00.0NaN3So0Dec
1863135546481278412750421798511A97622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1So0Dec
186487793788341100881363741A923622NaNNaNNaNNaN1NaNNaN2.04.00.0NaN2So0Dec
186593723418257140751950993A33632NaNNaNNaNNaN0NaNNaN2.03.00.0NaN2-10Dec
186669621406126060781155500A712622NaNNaNNaNNaN0NaNNaN0.0NaN0.0NaN1Di0Dec